/**
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or
 * (at your option) any later version.
 * 
 *  This program is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU General Public License for more details.
 *  
 *  You should have received a copy of the GNU General Public License
 *  along with this program; if not, write to the Free Software
 *  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
 */
package bots.mctsbot.ai.bots.bot.gametree.mcts.strategies.backpropagation;

import bots.mctsbot.ai.bots.bot.gametree.mcts.nodes.DecisionNode;
import bots.mctsbot.ai.bots.bot.gametree.mcts.nodes.OpponentNode;
import bots.mctsbot.ai.bots.util.RunningStats;

public class SampleWeightedBackPropStrategy implements BackPropagationStrategy {

	private final RunningStats stats = new RunningStats();

	public SampleWeightedBackPropStrategy() {
	}

	@Override
	public double getEV() {
		return stats.getMean();
	}

	@Override
	public int getNbSamples() {
		return stats.getNbSamples();
	}

	@Override
	public double getStdDev() {
		return stats.getStdDev();
	}

	@Override
	public double getEVStdDev() {
		return stats.getEVStdDev();
	}

	@Override
	public double getEVVar() {
		return stats.getEVVar();
	}

	@Override
	public double getVariance() {
		return stats.getVariance();
	}

	@Override
	public int getNbSamplesInMean() {
		return stats.getNbSamples();
	}

	@Override
	public void onBackPropagate(double value) {
		stats.add(value);
	}

	public static class Factory implements BackPropagationStrategy.Factory {

		@Override
		public SampleWeightedBackPropStrategy createForDecisionNode(DecisionNode node) {
			return new SampleWeightedBackPropStrategy();
		}

		@Override
		public SampleWeightedBackPropStrategy createForOpponentNode(OpponentNode node) {
			return new SampleWeightedBackPropStrategy();
		}

	}

}